1. Field of the Invention
The present invention relates to an image processing technique, and in particular to a method for recovering a compressed video signal and an apparatus therefor.
2. Description of the Prior Art
The image compression technique of MPEG, MPEG2, H261, H263, etc. is implemented by a Hybrid MC DCT (Motion Compensation Discrete Cosine Transform) technique. This hybrid MC DCT is classified into an encoding process and decoding processes. In the encoding process, the original image is divided into a plurality of blocks for compressing the information of a spacious region, and a two-dimensional DCT is performed with respect to each block, and a redundancy is decreased in the image of between the images using a correlation on a time axis between the images for decreasing the information of the time region. In addition, in the decoding process, the reverse sequence of the decoding process is performed. In order to implement the MCDCT technique, an encoder and decoder are required.
FIG. 1 is a block diagram illustrating a conventional image encoder. As shown therein, an input video signal is subtracted by a subtractor 1 with a motion compensated video signal from a video memory 9 and is inputted via a first switching unit 2 and a DCT unit 3. The DCT unit 3 processes the inputted video signal based on a DCT, and a quantization unit 4 quantizes a DCT-processed video signal and outputs a DCT coefficient q. This coefficient is reversely quantizated by a reverse quantizing unit 6 and is processed based on a reverse DCT by a reverse DCT unit 7 for thereby recovering the original video signal. The thusly recovered video signal is summed by a summing unit 8 with a video signal recovered in the earlier process via a second switching unit 10 and is inputted into the video memory. A controller 5 controls the first and second switching units 2 and 10 and transmits an intra/inter information (p=mtype; flag for INTRA/INTER), a transmission information (q; flag for transmitted or not), and an quantizing information (qz=Qp; quantizer indication) to a decoder (not shown in FIG. 1). The video memory 9 outputs a motion vector information (v=MV; motion vector) to the decoder. The DCT unit 3 outputs a DCT coefficient q to the decoder.
While the video signal is being coded, the information may be lost during the quantizing process. Therefore, the video signals reconstructed by the decoder may cause blocking artifacts and ring effects. The block artifacts occur when quantizing a low frequency DCT coefficient, and the ring effects occur due to the information loss of the original video in the quantizing process for a high frequency DCT coefficient.
Namely, in the case of the coding technique using a DCT in a system which is capable of coding a still picture or a motion picture, the entire image is divided into a plurality of small images (for example, 8×8 blocks), and then a transforming operation is performed with respect to the divided blocks, and the original image is processed based on a DCT, and an important information of the original image based on a result of the conversion is included in the low frequency component. As the component becomes high frequency, the important information is decreased. The low frequency component includes an information related to the neighboring block. The DCT transform is performed without considering a correlation between the blocks. Namely, the low frequency components are quantized by the blocks, so that a continuity between the neighboring blocks is lost. This phenomenon is called as the  referred to as blocking artifacts.
In addition, when quantizing the coefficients obtained when performing  from the DCT operation, as the interval of the quantizing operation is increased, the components to be coded is decreased. Therefore, the number of bits which will be processed is decreased, so that a  distortion occurs in the reconstructed original image. This phenomenon is called as the  referred to as ring effects. The ring effects, which occur when increasing the intervals of the quantizing operations, are increased at a contour line of an object among  in the images.
As a technique for removing the above-described block artifacts and ring effects, a low pass filter technique and a regularization recovering technique are generally used.
The low pass filter sets a filter tap or a filter coefficient based on or by selecting (filter mask) a plurality of pixels near a certain pixel and obtaining an average of the pixels. The recovered images are over smoothed in accordance with the kinds of images, and a compression ratio.
In the regularization recovering method, the block artifacts are adaptively processed in accordance with the statistical characteristic of the images. Namely, a  non-uniform information is all  computed at all direction boundary areas and in the interior of the block. However, since the computed values have a matrix form, it is impossible to implement a real time computation due to a  the large amount of computation. In addition, with an exception  except for the amount of non-uniformity, since an average is comprehensively adapted based on a result of the computation of the non-uniform information, in the block having a large amount of non-uniformity, the degree of the non-uniformity is decreased. On the contrary, the degree of the non-uniformity may be increased. Therefore, it is hard to say whether it is well adaptive  adapted well to the system.
The above-described two techniques have advantages and disadvantages in view of a complexity and performance increase of the system. Namely, the low pass filter technique has  requires less computation amount  compared to the regularization recovering technique and has , but has a small capacity for adaptively processing the images, so that the information is lost at an edge portion. The regularization recovering method has an  excellent performance and , but requires a large amount of computation when computing regularization parameters.